A dual self-attentive transformer U-Net model for precise pancreatic segmentation and fat fraction estimation

A dual self-attentive transformer U-Net model for precise pancreatic segmentation and fat fraction estimation

Abstract Accurately segmenting the pancreas from abdominal computed tomography (CT) images is crucial for detecting and managing pancreatic diseases, such as diabetes and tumors. Type 2 diabetes and metabolic syndrome are associated with pancreatic fat accumulation. Calculating the fat fraction aids...

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Bibliographic Details
Main Authors: Ashok Shanmugam, Prianka Ramachandran Radhabai, Kavitha KVN, Agbotiname Lucky Imoize
Format: Article
Language:English
Published: BMC 2025-08-01
Series:BMC Medical Imaging
Subjects:
Computed tomography (CT)
Pancreatic segmentation
Transformer Unet model
Attention mechanism
Fat fraction estimation
Online Access:https://doi.org/10.1186/s12880-025-01852-5
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https://doi.org/10.1186/s12880-025-01852-5

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